Fracton TechnologiesThe Cellular Symphony!
Innovative Solutions for Network Optimization
Authorized Partner
▪ A privately held company, headquartered in India
▪ Focused on innovations in RAN Optimization for GSM, UMTS & LTE Technologies
▪ Outstanding track record in offering Optimization Services to the leading operators
▪ Proud winner of 2015 Graham Bell Award for Best Telecom Product
About Us
The Company
The Team
▪ The team possesses world class expertise in –
▪ Planning & Management of Mobile Networks
▪ Design & Development of Telecom Products
▪ A fairly young, motivated and highly agile team
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Network Service Offerings
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GSM/UMTS/LTE Network Parametric Optimization
Radio Access Network Audit
Automatic Frequency Planning
Spectrum
Re-farming
Wide Range of Services offered by Fracton effectively addresses the challenges faced by Mobile Operators!
RAN Challenges faced by MNOs
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Inability to extract themaximum out of theinstalled RAN assetsdue to a number offactors!
RAN Asset Utilization
Improving KPI performance & fulfilling Regulator requirements on KPI Targets!
Improving KPIs
Customer has turned more Quality Conscious – Quality Differentiation is Vital!
Enhancing Customer
Experiences
Frequency Planning requirements are becoming more and more stringent due to reducing available spectrum on GSM!
Frequency Planning
RAN Challenges faced by MNOs (Cntd.)
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Carving out sizablechunk of spectrumwhile minimizing theimpact on QoS/QoEfor GSM traffic is amassive challenge!
Spectrum Refarming
Reliable & seamless QoE. Tackling complicated traffic planning & Interference Management is crucial for extracting the value of today’s Heterogeneous Landscape!
HetNetLandscape
Efficient traffic balancing & offloading to intra /inter technologies is crucial for handling exponential traffic increase!
Increased Data Traffic
Challenge
Widespread small cell deployment is the need of the hour but comes with a range of unique challenges!
Small Cell Integration
The Enabler!
MaxCell – Introduction
Spectrum
Refarming
Parametric
Optimization
Network
Consolidation
MaxCell – Core Philosophy
Each Cell is Unique!
So are each of its neighbor relationships!
Why to condemn them to a herd culture, then?
By leaving their critical parameters at their default levels!
Respect their individuality, instead!
Give them what they ask for… and allow your
network to perform at its best!
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Parametric Optimization
▪ An OSS based RAN Optimization Tool
▪ Addresses the Uniqueness of each Cell &
Neighbour
▪ Optimizes Network Performance & Quality of
Experience in a Flash!✓ Reduction in Customer Complaints
✓ Reduction in Call Drops
✓ Improvement in Voice Quality
✓ Reduction in Handover Failures
✓ Reduction in iRAT Handover Failures
✓ Improvement in Data Throughput
▪ Enables a Dynamic & Continuous Network
Optimization Regime
▪ Significant Capex & Opex Reduction
▪ Multi-vendor, Multi-technology Solution
MaxCell – Parametric Optimization
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Pre-Post KPI
Reports
OSS/NMS
Operator’s Configuration
Management
System
Operator’s Performance
Management
System
Performance Data
Existing Configuration
MR/Trace Data/ Traffic Recordings
Recommended Configuration
Traditional Way
Default Cell DB ParametersSet at Network Level
No Performance Gains
Manual Way
Optimized Cell DB Parameters on RNC/BSC or Cluster Level
Marginal Performance Gains
Automated Way
MaxCell Optimizes Per Cell/Per Neighbor Cell DB Parameters
Decisions Based on Radio Network Configuration & Performance Counters, KPIs & MRR Reports
Significant Performance Gains
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Why MaxCell ?
Automated Way of Cell Database Parameters Tuning
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MaxCell Solution is Based on Iterative Parameters Tuning Cycles
MaxCell 4G Optimization Cycle
MaxCell Inputs
Optimization Targets
Optimization Engine
Parameters Implementation
Performance Assessment
RSRP & Ant Para
Optimization
•Coverage Optimization
•No Dominance Optimization
•Pilot Pollution Optimization
•SINR & CQI Optimization
RF Performan
ce Optimizati
on
•Intra/Inter Frequency Cell Re-selection
•Inter RAT Cell Re-selection
•Inter RAT & Inter Frequency HO
•Intra Frequency HO Parameters
•DL & UL Throughput
LTE Key Features
•Carrier Aggregation
•MIMO
•CSFB & SRVCC
•HetNet – Small Cells
Neighbor List
•PCI Optimization
•Intra & Inter Frequency Neighbor Lists
•IRAT Neighbor Lists
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Typical Project Schedule – Improvements Observed in a Fortnight
MaxCell 4G Optimization Timelines
Week 1
•Selection of Optimization Area
•Existing Performance & KPI Assessment
•Define Optimization Targets – SINR, CQI, Layers Re-selection Criteria
•Schedule Traffic Recordings – MR & CQI
Week 2
•Import Network Configuration
•Import CM, PM & MR/Trace Recordings Data
•Run MaxCell Optimizer
•Generate Antenna Conf. & Cell Database Parameters Tuning Recommendations
Week 3-4
•Iteration 1a: Ant Conf & RSRP Power.
•Performance Data Collection for Iterations 1b, 1c & 1d – MR/Trace
•Iteration 1b: Intra Frequency & Inter RAT Cell Re-selection & HO Optimization
•Iteration 1c: Inter, Intra & Inter RAT Neighbor Lists Optimization
•Iteration 1d: Throughput DL & UL, Capacity, Features like MIMO, SRVCC, CSFB etc.
•Performance Data Collection for 2nd Iteration – MR/Trace & Counters
•Iteration 2 (Fine Tuning): Recommendations Generation & Implementation
Week 5
•Pre Post Performance Assessment
•Benchmarking
•Project Report Submission
MaxCell 4G Solution for ZTEData Input Requirements
• Configuration Dump– OSS XML Dump taken through OSS
Common Explorer
• Performance Counters & KPIs– OSS Counter Cell, Frequency Level & Per
Neighbour Level Stats
– 7 Working Days from 10 am to 10 pm
– NBH & BBH KPI Reports
• NetMax MR/CTS Recording– MR Recordings/Traces
• 3 Days & Hourly recordings from 11:00 am to 12:00 pm
Optimization Strategy: Exploiting Performance Counters & NetMax Recordings for
Assessing Traffic behavior which forms the basis for Optimization Algorithms.
MaxCell 4G Solution for NokiaData Input Requirements
• Configuration Dump– OSS XML Dump taken through OSS
Common Explorer
• Performance Counters & KPIs– OSS Counter Cell, Frequency Level & Per
Neighbour Level Stats
– 7 Working Days from 10 am to 10 pm
– NBH & BBH KPI Reports
• Megamon-Emil Recording– Layer 3 Cell Trace Recordings
• 3 Days & Hourly recordings from 11:00 am to 12:00 pm
Optimization Strategy: Exploiting Performance Counters & Megamon Recordings for
Assessing Traffic behavior which forms the basis for Optimization Algorithms.
MaxCell 4G Solution for HuaweiData Input Requirements
• Configuration Dump– CME Configuration Dump taken
through OSS
• Performance Counters & KPIs– OSS Counter Cell, Frequency Level & Per
Neighbour Level Stats– 7 Working Days from 10 am to 10 pm– NBH & BBH KPI Reports
• Huawei LTE Call Trace / CHR Recording– Layer 3 Cell Trace Recordings
• 3 Days & Hourly recordings from 11:00 am to 12:00 pm
Optimization Strategy: Exploiting Performance Counters & Traces Recordings for
Assessing Traffic & Inter Cell behavior which forms the basis for Optimization Algorithms.
MaxCell 4G Solution for EricssonData Input Requirements
• Configuration Dump– OSS XML Dump taken through OSS
Common Explorer
• Performance Counters & KPIs– OSS Counter Cell, Frequency Level & Per
Neighbour Level Stats
– 7 Working Days from 10 am to 10 pm
– NBH & BBH KPI Reports
• Ericsson LTE CTR Recordings– Layer-3 Trace Recordings
• 3 Days & Hourly recordings from 11:00 am to 12:00 pm
Optimization Strategy: Exploiting Performance Counters & Cell Trace Recordings for
Assessing Traffic & Inter Cell behavior which forms the basis for Optimization Algorithms.
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MaxCell Solution is Based on Iterative Parameters Tuning Cycles
MaxCell 3G Optimization Cycle
MaxCell Inputs
Optimization Targets
Optimization Engine
Parameters Implementation
Performance Assessment
CPICH & Ant Para
Optimization
•Coverage Optimization
•Pilot Pollution
•No Dominance Areas Optimization
Soft Handovers
•Cell Selection/ReSelection – Intra/Inter Freq
•Soft Handovers Parameters Optimization
•IRAT Cell Reselection & HO Optimization
•Inter Frequency HO Settings
Capacity & Admission
Control
•AC Thresholds
•Max Power Per Link / FACH Power
•HSDPA & DL Power
•Code Allocation
Neighbor List
•Scrambling Code Optimization
•Intra & Inter Frequency Neighbor Lists
•IRAT Neighbor Lists
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Typical Project Schedule – Improvements Observed in a Fortnight
MaxCell 3G Optimization Timelines
Week 1
•Selection of Optimization Area
•Existing Performance & KPI Assessment
•Define Optimization Targets – Voice Vs HSDPA
•Schedule Traffic Recordings – MR/Traces/Traffic Recording
Week 2
•Import Network Configuration
•Import CM, PM & Traffic Recordings Data
•Run MaxCell Optimizer
•Generate Antenna Conf. & Cell Database Parameter Recommendations
Week 3-4
•Iteration 1a: Ant Conf & CPICH Power.
•Performance Data Collection for Iterations 1b, 1c & 1d – MR/Traces/Traffic Recording
•Iteration 1b: Soft Handover, Inter Frequency & Inter RAT Performance Optimization
•Iteration 1c: Downlink/Uplink Capacity, HSDPA, Throughput Optimization
•Iteration 1d: Idle Mode & Neighbor List Optimization
•Performance Data Collection for 2nd Iteration – MR/Traces/Traffic Recording
•Iteration 2 (Fine Tuning): Recommendations Generation & Implementation
Week 5
•Pre Post Performance Assessment
•Benchmarking
•Project Report Submission
MaxCell 3G Solution for ZTEData Input Requirements
• Configuration Dump– OSS XML Dump taken through OSS
• Performance Counters & KPIs– OSS Counter Cell, Frequency Level & Per
Neighbour Level Stats
– 7 Working Days from 10 am to 10 pm
– NBH & BBH KPI Reports
• ZTE MR/CDT/Call Trace System (CTS)– MR/Layer 3 Cell Trace Recordings
• 3 Days & Hourly recordings from 11:00 am to 12:00 pm
Optimization Strategy: Exploiting Performance Counters & Trace Recordings for
Assessing Traffic & Inter Cell behavior which forms the basis for Optimization Algorithms.
MaxCell 3G Solution for NokiaData Input Requirements
• Configuration Dump– OSS XML Dump taken through OSS
Common Explorer
• Performance Counters & KPIs– OSS Counter Cell, Frequency Level & Per
Neighbour Level Stats– 7 Working Days from 10 am to 10 pm– NBH & BBH KPI Reports
• Megamon-Emil /CHR / MR Recordings– Layer 3 Cell Trace Recordings
• 3 Days & Hourly recordings from 11:00 am to 12:00 pm
Optimization Strategy: Exploiting Performance Counters & Megamon Recordings for
Assessing Traffic & Inter Cell behavior which forms the basis for Optimization Algorithms.
MaxCell 3G Solution for HuaweiData Input Requirements
• Configuration Dump– CME Configuration Dump taken
through OSS
• Performance Counters & KPIs– OSS Counter Cell, Frequency Level & Per
Neighbour Level Stats
– 7 Working Days from 10 am to 10 pm
– NBH & BBH KPI Reports
• Huawei CHR / PCHR Recording– Layer 3 Cell Trace Recordings
• 3 Days & Hourly recordings from 11:00 am to 12:00 pm
Optimization Strategy: Exploiting Performance Counters & Trace Recordings for
Assessing Traffic & Inter Cell behavior which forms the basis for Optimization Algorithms.
MaxCell 3G Solution for EricssonData Input Requirements
• Configuration Dump– OSS XML Dump taken through OSS
Common Explorer
• Performance Counters & KPIs– OSS Path:
/var/opt/ericsson/nms_umts_pms_seg/segment1/XML/– Counter Cell Level Data & Per Neighbor Level– 7 Working Days from 10 am to 10 pm– MO Classes: UtranCell, RncFunction, Hsdsch, Handover,
UtranRelation, GsmRelation– NBH & BBH KPI Reports
• GPEH Traffic Recording– WMRR & WNCS Recordings– GPEH data for RNC with filter
“RRC_Measurement_Reports”• 3 Days Hours Data from 11:00 am to 12:00 pm
Optimization Strategy: Exploiting Performance Counters & GPEH Traffic Recordings for
Assessing Traffic & Inter Cell behavior which forms the basis for Optimization Algorithms.
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MaxCell 2G Optimization Cycle
MaxCell Solution is Based on Iterative Parameters Tuning Cycles
MaxCell Inputs
Optimization Targets
Optimization Engine
Parameters Implementation
Performance Assessment
Frequency Fine Tuning
•RF Path Issues
•Interference Reduction
•Overshooting Cells Optimization
Handovers
•Handovers Parameters Optimization
•Neighbor List Optimization
•QOS Features Optimization
Traffic Balancing/
Capacity
•Dual Band Layers
•Traffic Balancing / Capacity
•QOS Features Optimization
•Hierarchical / IBC Cells Opt
Power Control
•Power Control Parameters Opt
•Interference Control
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Typical Project Schedule – Improvements Observed in a Fortnight
MaxCell 2G Optimization Timelines
Week 1
•Selection of Optimization Area
•Existing Performance & KPI Assessment
•Define Optimization Targets – DCR, Voice Quality & HOSR
•Schedule Traffic Recordings – MR / Traffic Recording
Week 2
•Import Network Configuration
•Import CM, PM & Traffic Recordings Data
•Run MaxCell Optimizer
•Generate Cell Database Parameter Recommendations
Week 3-4
•Iteration 1a: Freq Plan Fine Tuning & Neighbor List Tuning
•Performance Data Collection for Iterations 1b & 1c – In case Freq Plan Tuning is req.
•Iteration 1b: Traffic Balancing; Capacity Optimization; Dual Band Layers Opt
•Iteration 1c: Handover Performance, Power Control & QOS Features Optimization
•Performance Data Collection for 2nd Iteration – MR/Traffic Recordings & Counters
•Iteration 2 (Fine Tuning): Recommendations Generation & Implementation
Week 5
•Pre Post Performance Assessment
•Benchmarking
•Project Report Submission
Spectrum Refarming
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Spectrum Refarming- Challenges & Task
Complex Network Transformation
RF Redesign – Coverage & Capacity
Multiple AFP Implementations
Traffic Balancing Between Layers
Cell Database Parameters Tuning
Spectral Efficiency
User Perceived Quality Improvement
Quality
• Spectral Efficiency & Frequency Plan Approach
• Activation of QOS Enhancement Features
• Cell Database Parameters Tuning
Capacity
• Traffic Dimensioning on New Spectrum
• Offloading Traffic towards Different Technologies
• TRX Dimensioning
Coverage
Identify Coverage Deficient Areas & Recommendations
Spectrum Refarming Steps
• BSS Configuration Audit & Scenarios Identification– Analysis of Existing Radio Network Configuration– Identification of Different Spectrum Re-farming Scenarios
• Site Configurations – Underlay/Overlay; Band Segregation between BCCH/TCH• TRX Dimensioning• AMR HR Usage Thresholds• Traffic Sharing with LTE/UMTS• Traffic Handling Capacity / Utilization
• Measurement Reports Recordings– MR Data Collection for 2-3 Days on Existing Network – Creation for Project for Various Scenarios
• Running Simulations– KPI Performance Prediction for different Scenarios– Coverage & Capacity Sites Identification using Heat Maps– Identification of Optimum Re-farming Strategy/Scenario– Identification of BoQ
• Spectrum Re-farming– AFP– Neighbor List
• Cell Database Parameter Optimization– Frequency plan Fine-tuning– Parametric Optimization
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Parametric Optimization
Spectrum Re-farming
Running Simulations
Measurement Reports Recordings
BSS Configuration Audit & Scenarios Identification
Traffic & Coverage Heat Maps
• MaxCell’s Optimization & Analytics Modules are also tailor-made for Spectrum Re-farming related Activities– Capable of Generation of Traffic & Coverage Heat Maps based on Traffic/Trace Recordings
captured on OEMs OSS e.g. Ericsson MRR & NCS Recordings– Sophisticated Proprietary Algorithms for Generating Traffic & Coverage Heat Maps on GIS Tool – Easy Visualization– Accurately Locates Coverage Gaps– Ability to Generate Coverage Heat Maps for Various Re-farming Scenarios – Aids in Visualization of High Traffic Carrying Areas
• Use Cases– Identification of Poor Coverage Areas for Underlay/Overlay/BCCH 900/BCCH 1800– Depiction of Coverage in different Spectrum Re-farming Scenarios– New Coverage Sites Planning – Placement of Sites on GIS-Map
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Coverage Heat Map Analysis
Heat Map – Existing 900 Band Underlay
Heat Map – Re-farmed Conversion of 900 Band Underlay to 1800 Band Underlay
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Automatic Frequency Planning
AFP – Introduction
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✓ A Multi-Vendor Automatic Frequency Planning
✓ Based on Mobile Measurement Reports Captured
✓ Improves Spectral Efficiency & Capacity
✓ Optimizes Network Performance KPIs➢ Drop Call Rate
➢ Voice Quality (RxQual)
➢ Handover Success Rate
➢ TCH Assignment Success Rate
AFP Cycle
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•Configuration & Performance Data
•Site Database
•BSIC Tuning
Preparation
•Network Freeze
•MR & HO Data Collection
Traffic Recordings •Data Processing
•Model Creation & Evaluation
IM Generation
•FP Generation
•Neighbor Plan Generation
FP Iterations•FP & Neighbor Plan Download
•Overshooting/Swap Cell Correction
•Physical Optimization
Implementation
Case Studies
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Case Study – Parametric Optimization (LTE)
Leading Operator - Overall LTE Pre – Post KPIs
(5 Working Days Average)
Radio Drops reduced by 15%
• Tx Power Optimization
• RS Power Optimization (Pa & Pb)
• Antenna Configuration Optimization
• Cell & Neighbor Level Parameters Tuning
• RRM Parameters
• PRACH Optimization
• UL Power Control
• PCI & Neighbor Relation Fine Tuning
• Mobility Robustness and iRAT Optimization
• Features Fine-Tuning
Performance Optimization Areas
• Radio Environment
• Maximized SINR and CQI
• Maximized Cell Edge Performance
• Improved UL Noise Rise and UL RSSI
• Key Performance Indicators
• Significant Performance Gains in following KPIs:
• Accessibility- Setup Success Rate
• Retainability- Drop Call Rate
• Handover Success Rate- Inter/Intra
• DL/UL Throughput
Gains
• Based on Live Network Performance Statistics & Traffic Recordings• Modeling the Performance at different Levels
• Per Cell• Per Carrier• Neighbor Relations – Intra & Inter RAT
• Performance Data Capture Duration• Performance Raw Statistics – 7 to 14 Days• Traffic / Trace Recordings – 3 to 5 Days
Core Optimization Concept
Summary - QoS NBH
UL RSSI reduced by 1.3 dB
Intra System HO Failure Rate reduced by 16.9%
DL Throughput increased by 11.5%
UL Throughput increased by 9.3%
Case Study – Parametric Optimization (UMTS)
• Pilot Pollution & Soft Handover Gains
• Antenna Configuration Optimization
• CPICH Power & Cell Individual Offset
• Cell & Per Neighbor Level Parameters Tuning
• RACH Optimization
• Cell Capacity
• Inter System iRAT & Inter Freq - qRxlevMin
• Soft Handovers Parameters Optimization
• Cell Coverage Shaping – Cell Individual Offsets
• Per Neighbor Relation Thresholds Setting
• reportingRange, TimeToTrigger, qOffsetxsn
• HSDPA
• Power Optimization / PDSCH Codes
Performance Optimization Areas
• Resource Utilization
• Maximization & Optimum Usage of RF Network Resources
• CAPEX & OPEX Reduction
• Key Performance Indicators
• Significant Performance Gains in following KPIs:
• RRC & RAB Setup Success Rate for CS & HSDPA
• Soft Handover Success Rate
• RAB Drop Call Rate for CS & HSDPA
• BLER Performance
• HSDPA Throughput
• Customer Experience
• Marked Improvement in KQIs
Gains
• Based on Live Network Performance Statistics & Traffic Recordings• Modeling the Performance at different Levels
• Per Cell• Multi Carrier Level• Traffic Level
• Per Neighbor Relation• Performance Data Capture Duration
• Performance Raw Statistics – 7 to 14 Days• Traffic / Trace Recordings – 3 to 5 Days
Core Optimization Concept
0
0.5
1
1.5
2
2.5
RRCSetupFailureRateCS
RRCSetupFailureRatePS
RABDroppedCallRateCS
RABDroppedCallRatePS
Pre
Post
Leading Operator - Overall UMTS Pre – Post NBH KPIs (5 Working Days Average)
Significant Improvement is observed in all five KPIs
1840
1860
1880
1900
1920
1940
1960
1980
2000
2020
Pre Post
HSThroughputKbps
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Case Study – Parametric Optimization (GSM)
Leading Operator - Overall GSM Pre – Post NBH KPIs
(5 Working Days Average)
The overall improvement in TCH Drop is 33%. Downlink Quality performance has also Improved and Bad Quality Samples reduced by 17%
96.50
97.00
97.50
98.00
98.50
99.00
99.50
CallComple on
Rate
HOSR GoodDLRxqual%
GoodULRxqual%
98.95
97.4497.29
97.71
99.30
97.80 97.75 97.81
Pre
Post
0.50
0.60
0.70
0.80
0.90
1.00
1.10
1.20
AverageofTCHDrop
AverageofSDDrop
1.051.11
0.70
1.07
Pre
Post
• Frequency Fine Tuning
• Optimization of ARFCN Assignment on BCCH & TCH
Layers on 10% of the Cells
• Cell & Per Neighbor Level Parameters Tuning
• Dual Band Layers – Traffic Balancing
• Handover Performance
• Handover Trigger Thresholds
• Cell Coverage Shaping – Tuning Offsets
• Per Neighbor Relation Thresholds Setting
• QoS Enhancement Features
• Activation of Features e.g. PS DL Power Control
• Repeated SAACH/FAACH
Performance Optimization Areas
• Resource Utilization
• Maximization & Optimum Usage of RF Network Resources
• CAPEX & OPEX Reduction
• Key Performance Indicators
• Significant Performance Gains in following KPIs:
• Drop Call Rate
• Handover Success Rate
• TCH Assignment Success Rate
• Good Voice Quality Samples
• Customer Experience
• Marked Improvement in KQIs
Gains
• Based on Live Network Performance Statistics & Traffic Recordings• Modeling the Performance at different Levels
• Per Cell• Dual Band Layers• BCCH; TCH 900 & TCH 1800
• Per Neighbor Relation• Performance Data Capture Duration
• Performance Raw Statistics – 7 to 14 Days• Traffic / Trace Recordings – 3 to 5 Days
Core Optimization Concept
Summary - QoS NBH
Case Study 2 – Parametric Optimization (GSM)
Summary - QoS NBH & BBH
✓ Project Delivered for a Tier-1 Operator✓ Network Size- 4000+ Sites ✓ Site Configuration- 900M & 900+1800M✓ 3 Cycles of AFP and Automatic Parameter
Optimization Using MaxCell were Performed ✓ Significant Improvement Achieved in all
Major KPIs, NQI and Customer Complaints✓ Project Highlights:
✓ 28% Improvement in DLQ✓ 21% Improvement in DCR✓ 37% Improvement in Cells Meeting All
KPIs
Defaulter Cells in BBH
Case Study 2 – Parametric Optimization (GSM)
Summary- NQI & Customer Complaints
✓ Project Highlights:✓ Significant Improvement in Voice &
Data NQI✓ 142% Jump in Voice NQI✓ 37% Improvement in Cells Meeting
All KPIs ✓ 42% Jump in Overall NQI✓ 54% Reduction in Customer
Complaints Due to Radio Issues
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Case Study – Spectrum Refarming
Summary- QoS ✓ Project Delivered for a Tier-1 Operator ✓ Refarming- 5MHz Spectrum Carved from
1800MHz✓ Network Size- 4500+ Sites ✓ Site Configuration- 900M & 900+1800M✓ Even after Spectrum Reduction Major KPIs
Were Restored to Previous Level. In Few KPIs Improvement was Achieved
✓ Project Highlights:✓ 5MHz Spectrum Carved from GSM for
LTE Deployment Without Impacting GSM Network’s Existing QoS
✓ Significant Improvement Achieved in SD Drop Rate- 12%
Case Study – AFP
Summary- QoS
✓ Project Delivered for a Tier-1 Operator✓ Network Size- 5700+ Sites ✓ Site Configuration- 900M, 1800M &
900+1800M✓ Significant Improvement Achieved in all
Major KPIs✓ Project Highlights:
✓ 75%+ Defaulting Cells Shown Improvement- DLQ and ULQ
✓ 35%+ Reduction in Defaulters DLQ✓ 28%+ Reduction in Defaulters ULQ
Defaulter Cells in BBH
Case Study – AFP
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Significant improvement in Pre AFP DLQ Defaulter Cells▪ More than 80% defaulter Cells have shown improvement Post AFP
▪ More than 35% reduction in defaulter Cells count Post AFP
Improvement in defaulter cells in DL RxQual
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Improvement in defaulter cells in UL RxQual
Significant improvement in Pre AFP ULQ Defaulter Cells▪ More than 79% defaulter Cells have shown improvement Post AFP
▪ More than 28% reduction in defaulter Cells count Post AFP
Case Study – AFP
KPI Name Pre (NBH) Post (NBH) Improvement (%)
TCH Drop Rate 0.91 0.7 23.08
SD Drop Rate 0.52 0.41 21.15
HO Failure Rate 2.03 1.81 10.84
TCH Assignment Failure Rate 0.5 0.41 18.00
RxQual DL – Bad (6&7) 2.98 2.16 27.52
RxQual UL – Bad (6&7) 2.32 2.05 11.64
Call Setup Failure Rate 0.81 0.68 16.05
(A) Tier 1 Operator, Asia
Network Size: GSM 8000 Cells
Scope of Work: Automatic Frequency Planning, Automatic Neighbour Planning, Overshooting Cell Correction, Swapped Sector Correction, Cell Database Parameter Optimization, QoS related Features & Functionality enabling/fine-tuning, Core Network troubleshooting, Transport Network troubleshooting.
Duration: 16 weeks
KPIs Improved:
Summary of Few Recent Projects
(B) Tier 1 Operator, Asia
KPI Name Pre (NBH) Post (NBH) Improvement (%)
RRC Setup Failure Rate CS 0.68 0.52 23.53
RRC Setup Failure Rate PS 1.44 1.29 10.42
Soft HO Failure Rate 3.62 2.45 32.32
RAB Dropped Call Rate CS 0.79 0.6 24.05
RAB Dropped Call Rate PS 2.25 1.9 15.56
Data Throughput – DL (Mbps) 18.51 20.13 8.75
Network Size: UMTS 10000 Cells
Scope of Work: Automatic PSC Planning, Automatic Neighbour Planning, Overshooting Cell Correction, Swapped Sector Correction, Cell Database Parameter Optimization, Antenna Physical Parameter Optimization
Duration: 18 weeks
KPIs Improved:
(C) Tier 1 Operator, Africa
KPI Name Pre (NBH) Post (NBH) Improvement
RRC Establishment Fail Rate 0.75% 0.67% 10.66%
e-RAB Drop Rate 1.40% 1.10% 21.42%
Handover Failure Rate 2.95% 2.25% 23.72%
Maximum Cell DL PDCP Throughput 33 Mbps 41 Mbps 24.24%
Maximum Cell UL PDCP Throughput 9.5 Mbps 10.45 Mbps 10.55%
Network Size: LTE 3500 Cells
Scope of Work: Automatic PCI Planning, Automatic Neighbour Planning, Overshooting Cell Correction, Swapped Sector Correction, Cell Database Parameter Optimization, Antenna Physical Parameter Optimization
Duration: 12 weeks
KPIs Improved:
Fracton Technologies
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Authorized PartnerAuthorized Partner
Authorized Partner: Email: [email protected]: www.tarec-in.com